• Graph Neural Networks with Parallel Local Neighborhood Aggregations 

      Doshi, Siddhanth Rahul
      Graph neural networks (GNNs) have become very popular for processing and analyzing graph-structured data in the last few years. Using message passing as their basic building blocks that aggregate information from neighborhoods, ...
    • Learning with Multi-domain and Multi-view Graph Data 

      Kadambari, Sai Kiran
      In many applications, we observe large volumes of data supported on irregular (non-Euclidean) domains. In graph signal processing (GSP) and graph machine learning (GML), data is indexed using the nodes of a graph and ...